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Abstract Alzheimer's disease (AD) has emerged as the most prevalent and complex neurodegenerative disorder among the elderly population. However, the genetic comorbidity etiology for AD remains poorly understood. In this study, we conducted pleiotropic analysis for 41 AD phenotypic comorbidities, identifying ten genetic comorbidities with 16 pleiotropy genes associated with AD. Through biological functional and network analysis, we elucidated the molecular and functional landscape of AD genetic comorbidities. Furthermore, leveraging the pleiotropic genes and reported biomarkers for AD genetic comorbidities, we identified 50 potential biomarkers for AD diagnosis. Our findings deepen the understanding of the occurrence of AD genetic comorbidities and provide new insights for the search for AD diagnostic markers. Graphical Abstract Study pipeline.

Abstract Age-related cataract and hearing difficulties are major sensory disorders that often co-exist in the global-wide elderly and have a tangible influence on the quality of life. However, the epidemiologic association between cataract and hearing difficulties remains unexplored, while little is known about whether the two share their genetic etiology. We first investigated the clinical association between cataract and hearing difficulties using the UK Biobank covering 502,543 individuals. Both unmatched analysis (adjusted for confounders) and a matched analysis (one control matched for each patient with cataract according to confounding factors) were undertaken and confirmed that cataract was associated with hearing difficulties (OR, 2.12; 95% CI, 1.98–2.27; OR, 2.03; 95% CI, 1.86–2.23, respectively). Furthermore, we explored and quantified the shared genetic architecture of these two complex sensory disorders at the common variant level using the bivariate causal mixture model (MiXeR) and conditional/conjunctional false discovery rate method based on the largest available genome-wide association studies of cataract (N = 585,243) and hearing difficulties (N = 323,978). Despite detecting only a negligible genetic correlation, we observe polygenic overlap between cataract and hearing difficulties and identify 6 shared loci with mixed directions of effects. Follow-up analysis of the shared loci implicates candidate genes QKI, STK17A, TYR, NSF, and TCF4 likely contribute to the pathophysiology of cataracts and hearing difficulties. In conclusion, this study demonstrates the presence of epidemiologic association between cataract and hearing difficulties and provides new insights into the shared genetic architecture of these two disorders at the common variant level.

Abstract Background Little is known regarding the leading risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without APOE4. The identification of key risk factors for dementia/Alzheimer’s disease (AD) in individuals with and without the APOE4 gene is of significant importance in global health. Methods Our analysis included 110,354 APOE4 carriers and 220,708 age- and sex-matched controls aged 40–73 years at baseline (between 2006–2010) from UK Biobank. Incident dementia was ascertained using hospital inpatient, or death records until January 2021. Individuals of non-European ancestry were excluded. Furthermore, individuals without medical record linkage were excluded from the analysis. Moderation analysis was tested for 134 individual factors. Results During a median follow-up of 11.9 years, 4,764 cases of incident all-cause dementia and 2065 incident AD cases were documented. Hazard ratios (95% CIs) for all-cause dementia and AD associated with APOE4 were 2.70(2.55–2.85) and 3.72(3.40–4.07), respectively. In APOE4 carriers, the leading risk factors for all-cause dementia included low self-rated overall health, low household income, high multimorbidity risk score, long-term illness, high neutrophil percentage, and high nitrogen dioxide air pollution. In non-APOE4 carriers, the leading risk factors included high multimorbidity risk score, low overall self-rated health, low household income, long-term illness, high microalbumin in urine, high neutrophil count, and low greenspace percentage. Population attributable risk for these individual risk factors combined was 65.1%, and 85.8% in APOE4 and non-APOE4 carriers, respectively. For 20 risk factors including multimorbidity risk score, unhealthy lifestyle habits, and particulate matter air pollutants, their associations with incident dementia were stronger in non-APOE4 carriers. For only 2 risk factors (mother’s history of dementia, low C-reactive protein), their associations with incident all-cause dementia were stronger in APOE4 carriers. Conclusions Our findings provide evidence for personalized preventative approaches to dementia/AD in APOE4 and non-APOE4 carriers. A mother’s history of dementia and low levels of C-reactive protein were more important risk factors of dementia in APOE4 carriers whereas leading risk factors including unhealthy lifestyle habits, multimorbidity risk score, inflammation and immune-related markers were more predictive of dementia in non-APOE4 carriers.

Abstract Background Multimorbidity is better prevented in younger ages than in older ages. This study aims to identify the differences in comorbidity patterns in middle-aged inpatients from China and the United Kingdom (UK). Methods We utilized 184,133 and 180,497 baseline hospitalization records in middle-aged populations (40–59 years) from Shaanxi, China, and UK Biobank. Logistic regression was used to calculate odds ratios and P values for 43,110 unique comorbidity patterns in Chinese inpatients and 21,026 unique comorbidity patterns in UK inpatients. We included the statistically significant (P values adjusted by Bonferroni correction) and common comorbidity patterns (the pattern with prevalence > 1/10,000 in each dataset) and employed network analysis to construct multimorbidity networks and compare feature differences in multimorbidity networks for Chinese and UK inpatients, respectively. We defined hub diseases as diseases having the top 10 highest number of unique comorbidity patterns in the multimorbidity network. Results We reported that 57.12% of Chinese inpatients had multimorbidity, substantially higher than 30.39% of UK inpatients. The complete multimorbidity network for Chinese inpatients consisted of 1367 comorbidities of 341 diseases and was 2.93 × more complex than that of 467 comorbidities of 215 diseases in the UK. In males, the complexity of the multimorbidity network in China was 2.69 × more than their UK counterparts, while the ratio was 2.63 × in females. Comorbidities associated with hub diseases represented 68.26% of comorbidity frequencies in the complete multimorbidity network in Chinese inpatients and 55.61% in UK inpatients. Essential hypertension, dyslipidemia, type 2 diabetes mellitus, and gastritis and duodenitis were the hub diseases in both populations. The Chinese inpatients consistently demonstrated a higher frequency of comorbidities related to circulatory and endocrine/nutritional/metabolic diseases. In the UK, aside from these comorbidities, comorbidities related to digestive and genitourinary diseases were also prevalent, particularly the latter among female inpatients. Conclusions Chinese inpatients exhibit higher multimorbidity prevalence and more complex networks compared to their UK counterparts. Multimorbidity with circulatory and endocrine/nutritional/metabolic diseases among both Chinese and UK inpatients necessitates tailored surveillance, prevention, and intervention approaches. Targeted interventions for digestive and genitourinary diseases are warranted for the UK.

Abstract Objective To evaluate the association of atherosclerotic cardiovascular disease (ASCVD) risk factors with incident ASCVD events among type 2 diabetes (T2D) individuals with microvascular complications. Methods We included T2D participants with only microvascular complications from the UK Biobank cohort at baseline (2006–2010). Multivariable-adjusted Cox proportional hazards models were used to study the association between ASCVD risk factors with adjudicated incident ASCVD in T2D participants with only microvascular complications. A restricted cubic spline approach was employed to evaluate potential nonlinear associations between ASCVD risk factors and ASCVD. Results We studied 4,129 T2D individuals with microvascular complications at baseline. Over a median follow-up of 11.7 years, a total of 1,180 cases of incident ASCVD were documented, of which 1,040 were CHD, 100 were stroke, and 40 were both CHD and stroke events. After multivariable-adjustment, high-density lipoprotein cholesterol (HDL-C) level was linearly associated with a decreased risk of incident ASCVD [hazard ratio (HR): 0.49, 95% Confidence interval (CI): 0.32–0.75, Plinear = 0.011] and each 10 nmol/L increase of lipoprotein(a) [Lp(a)] level (HR: 1.02, 95% CI: 1.00-1.04, Plinear = 0.012) was linearly associated with an increased risk of incident ASCVD in T2D participants with only microvascular complications. Conclusion HDL-C levels and Lp(a) levels (per 10 nmol/L) showed an independent linear relation with ASCVD risk among T2D individuals with only microvascular complications at long-term follow-up.

Abstract Background Little is known regarding whether sex assigned at birth modifies the association between several predictive factors for dementia and the risk of dementia itself. Methods Our retrospective cohort study included 214,670 men and 214,670 women matched by age at baseline from the UK Biobank. Baseline data were collected between 2006 and 2010, and incident dementia was ascertained using hospital inpatient or death records until January 2021. Mediation analysis was tested for 133 individual factors. Results Over 5,117,381 person-years of follow-up, 5928 cases of incident all-cause dementia (452 cases of young-onset dementia, 5476 cases of late-onset dementia) were documented. Hazard ratios (95% CI) for all-cause, young-onset, and late-onset dementias associated with the male sex (female as reference) were 1.23 (1.17–1.29), 1.42 (1.18–1.71), and 1.21 (1.15–1.28), respectively. Out of 133 individual factors, the strongest mediators for the association between sex and incident dementia were multimorbidity risk score (percentage explained (95% CI): 62.1% (45.2–76.6%)), apolipoprotein A in the blood (25.5% (15.2–39.4%)), creatinine in urine (24.9% (16.1–36.5%)), low-density lipoprotein cholesterol in the blood (23.2% (16.2–32.1%)), and blood lymphocyte percentage (21.1% (14.5–29.5%)). Health-related conditions (percentage (95% CI) explained: 74.4% (51.3–88.9%)) and biomarkers (83.0% (37.5–97.5%)), but not lifestyle factors combined (30.1% (20.7–41.6%)), fully mediated sex differences in incident dementia. Health-related conditions combined were a stronger mediator for late-onset (75.4% (48.6–90.8%)) than for young-onset dementia (52.3% (25.8–77.6%)), whilst lifestyle factors combined were a stronger mediator for young-onset (42.3% (19.4–69.0%)) than for late-onset dementia (26.7% (17.1–39.2%)). Conclusions Our analysis matched by age has demonstrated that men had a higher risk of all-cause, young-onset, and late-onset dementias than women. This association was fully mediated by health-related conditions or blood/urinary biomarkers and largely mediated by lifestyle factors. Our findings are important for understanding potential mechanisms of sex in dementia risk.

Abstract Background The aim of this study is to investigate the association of retinal age gap with the risk of incident stroke and its predictive value for incident stroke. Methods A total of 80,169 fundus images from 46,969 participants in the UK Biobank cohort met the image quality standard. A deep learning model was constructed based on 19,200 fundus images of 11,052 disease-free participants at baseline for age prediction. Retinal age gap (retinal age predicted based on the fundus image minus chronological age) was generated for the remaining 35,917 participants. Stroke events were determined by data linkage to hospital records on admissions and diagnoses, and national death registers, whichever occurred earliest. Cox proportional hazards regression models were used to estimate the effect of retinal age gap on risk of stroke. Logistic regression models were used to estimate the predictive value of retinal age and well-established risk factors in 10-year stroke risk. Results A total of 35,304 participants without history of stroke at baseline were included. During a median follow-up of 5.83 years, 282 (0.80%) participants had stroke events. In the fully adjusted model, each one-year increase in the retinal age gap was associated with a 4% increase in the risk of stroke (hazard ratio [HR] = 1.04, 95% confidence interval [CI]: 1.00–1.08, P = 0.029). Compared to participants with retinal age gap in the first quintile, participants with retinal age gap in the fifth quintile had significantly higher risks of stroke events (HR = 2.37, 95% CI: 1.37–4.10, P = 0.002). The predictive capability of retinal age alone was comparable to the well-established risk factor-based model (AUC=0.676 vs AUC=0.661, p=0.511). Conclusions We found that retinal age gap was significantly associated with incident stroke, implying the potential of retinal age gap as a predictive biomarker of stroke risk.

Abstract Background Dual sensory impairment is affecting over 10% of older adults worldwide. However, the long-term effect of dual sensory impairment (DSI) on the risk of mortality remains controversial. We aim to investigate the impact of single or/and dual sensory impairment on the risk of mortality in a large population-based sample of the adult in the UK with 14-years of follow-up. Methods This population-based prospective cohort study included participants aged 40 and over with complete records of visual and hearing functions from the UK Biobank study. Measurements of visual and hearing functions were performed at baseline examinations between 2006 and 2010, and data on mortality was obtained by 2021. Dual sensory impairment was defined as concurrent visual and hearing impairments. Cox proportional hazards regression models were employed to evaluate the impact of sensory impairment (dual sensory impairment, single visual or hearing impairment) on the hazard of mortality. Results Of the 113,563 participants included in this study, the mean age (standard deviation) was 56.8 (8.09) years, and 61,849 (54.5%) were female. At baseline measurements, there were 733 (0.65%) participants with dual sensory impairment, 2,973 (2.62%) participants with single visual impairment, and 13,560 (11.94%) with single hearing impairment. After a follow-up period of 14 years (mean duration of 11 years), 5,992 (5.28%) participants died from all causes. Compared with no sensory impairment, dual sensory impairment was significantly associated with an estimated 44% higher hazard of mortality (hazard ratio: 1.44 [95% confidence interval, 1.11–1.88], p = 0.007) after multiple adjustments. Conclusions Individuals with dual sensory impairment were found to have an independently 44% higher hazard of mortality than those with neither sensory impairment. Timely intervention of sensory impairment and early prevention of its underlying causes should help to reduce the associated risk of mortality.

Abstract Background Plasma metabolomic profile is disturbed in dementia patients, but previous studies have discordant conclusions. Methods Circulating metabolomic data of 110,655 people in the UK Biobank study were measured with nuclear magnetic resonance technique, and incident dementia records were obtained from national health registers. The associations between plasma metabolites and dementia were estimated using Cox proportional hazard models. The 10-fold cross-validation elastic net regression models selected metabolites that predicted incident dementia, and a 10-year prediction model for dementia was constructed by multivariable logistic regression. The predictive values of the conventional risk model, the metabolites model, and the combined model were discriminated by comparison of area under the receiver operating characteristic curves (AUCs). Net reclassification improvement (NRI) was used to estimate the change of reclassification ability when adding metabolites into the conventional prediction model. Results Amongst 110,655 participants, the mean (standard deviation) age was 56.5 (8.1) years, and 51 186 (46.3%) were male. A total of 1439 (13.0%) developed dementia during a median follow-up of 12.2 years (interquartile range: 11.5–12.9 years). A total of 38 metabolites, including lipids and lipoproteins, ketone bodies, glycolysis-related metabolites, and amino acids, were found to be significantly associated with incident dementia. Adding selected metabolites (n=24) to the conventional dementia risk prediction model significantly improved the prediction for incident dementia (AUC: 0.824 versus 0.817, p =0.042) and reclassification ability (NRI = 4.97%, P = 0.009) for identifying high risk groups. Conclusions Our analysis identified various metabolomic biomarkers which were significantly associated with incident dementia. Metabolomic profiles also provided opportunities for dementia risk reclassification. These findings may help explain the biological mechanisms underlying dementia and improve dementia prediction.

Abstract Background Little is known regarding life-course trajectories of important diseases. We aimed to identify diseases that were strongly associated with mortality and test temporal trajectories of these diseases before mortality. Methods Our analysis was based on UK Biobank. Diseases were identified using questionnaires, nurses’ interviews, or inpatient data. Mortality register data were used to identify mortality up to January 2021. The association between 60 individual diseases at baseline and in the life course and incident mortality was examined using Cox proportional regression models. Those diseases with great contribution to mortality were identified and disease trajectories in life course were then derived. Results During a median follow-up of 11.8 years, 31,373 individuals (median age at death (interquartile range): 70.7 (65.3–74.8) years, 59.4% male) died of all-cause mortality (with complete data on diagnosis date of disease), with 16,237 dying with cancer and 6702 with cardiovascular disease (CVD). We identified 37 diseases including cancers and heart diseases that were associated with an increased risk of mortality independent of other diseases (hazard ratio ranged from 1.09 to 7.77). Among those who died during follow-up, 2.2% did not have a diagnosis of any disease of interest and 90.1% were diagnosed with two or more diseases in their life course. Individuals who were diagnosed with more diseases in their life course were more likely to have longer longevity. Cancer was more likely to be diagnosed following hypertension, hypercholesterolemia, CVD, or digestive disorders and more likely to be diagnosed ahead of CVD, chronic kidney disease (CKD), or digestive disorders. CVD was more likely to be diagnosed following hypertension, hypercholesterolemia, or digestive disorders and more likely to be diagnosed ahead of cancer or CKD. Hypertension was more likely to precede other diseases, and CKD was more likely to be diagnosed as the last disease before more mortality. Conclusions There are significant interplays between cancer and CVD for mortality. Cancer and CVD were frequently clustered with hypertension, CKD, and digestive disorders with CKD highly being diagnosed as the last disease in the life course. Our findings underline the importance of health checks among middle-aged adults for the prevention of premature mortality.

Abstract Background Identifying leading dietary determinants for cardiometabolic risk (CMR) factors is urgent for prioritizing interventions in children. We aimed to identify leading dietary determinants for the change in CMR and create a healthy diet score (HDS) to predict CMR in children. Methods We included 5676 children aged 6–13 years in the final analysis with physical examinations, blood tests, and diets assessed at baseline and one year later. CMR score (CMRS) was computed by summing Z-scores of waist circumference, an average of systolic and diastolic blood pressure (SBP and DBP), fasting glucose, high-density lipoprotein cholesterol (HDL-C, multiplying by − 1), and triglycerides. Machine learning was used to identify leading dietary determinants for CMR and an HDS was then computed. Results The nine leading predictors for CMRS were refined grains, seafood, fried foods, sugar-sweetened beverages, wheat, red meat other than pork, rice, fungi and algae, and roots and tubers with the contribution ranging from 3.9 to 19.6% of the total variance. Diets high in seafood, rice, and red meat other than pork but low in other six food groups were associated with a favorable change in CMRS. The HDS was computed based on these nine dietary factors. Children with HDS ≥8 had a higher decrease in CMRS (β (95% CI): − 1.02 (− 1.31, − 0.73)), BMI (− 0.08 (− 0.16, − 0.00)), SBP (− 0.46 (− 0.58, − 0.34)), DBP (− 0.46 (− 0.58, − 0.34)), mean arterial pressure (− 0.50 (− 0.62, − 0.38)), fasting glucose (− 0.22 (− 0.32, − 0.11)), insulin (− 0.52 (− 0.71, − 0.32)), and HOMA-IR (− 0.55 (− 0.73, − 0.36)) compared to those with HDS ≦3. Improved HDS during follow-up was associated with favorable changes in CMRS, BMI, percent body fat, SBP, DBP, mean arterial pressure, HDL-C, fasting glucose, insulin, and HOMA-IR. Conclusion Diets high in seafood, rice, and red meat other than pork and low in refined grains, fried foods, sugar-sweetened beverages, and wheat are leading healthy dietary factors for metabolic health in children. HDS is strongly predictive of CMR factors.

Abstract Background Malleolar fracture, which is present in 37–53% of human ankle osteoarthritis (OA), is the most common type of fracture in the ankle joint. In spite of this, no rat animal model has been developed for this type of injury to date. Here, we established a rat ankle post-traumatic OA (PTOA) model induced by malleolar fracture; this model will be useful in ankle OA research. Methods Two-month-old male Sprague Dawley (SD) rats were randomized into 2 groups (n = 19 per group): 1) malleolus articular fracture, dislocation, and immediate reduction on the right joints and 2) malleolus articular fracture on the right ankle. The contralateral ankle joints were used as controls. The fracture and healing processes were confirmed and monitored by radiography. Changes in inflammation were monitored in vivo by fluorescence molecular tomography (FMT). Cartilage damage and changes in expression of OA-related genes were analyzed by histology, immunohistochemistry, Real-time quantitative PCR (qPCR) and enzyme-linked immunosorbent assay (ELISA) at 8 weeks post-surgery. Results X-rays showed that all fractures were healed at 8 weeks post-surgery. A reproducible, mild to moderate degree of OA cartilage damage with reduced aggrecan was detected by histology in all animals in both groups but there was no significant difference between the two groups. Decreased Col-II and increased Col-X and MMP-13 levels were detected by qPCR, immunohistochemistry, ELISA and FMT from both groups cartilage. Conclusions Malleolus articular fracture alone induces ankle OA with lesions on the central weight bearing area of the tibiotalar joint in rats. This model will provide a reproducible and useful tool for researchers to study ankle OA.